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Imagine for a minute that you could know what’s your client favorite restaurant, how much does he like to spend there and how often does he go…. Imagine that you could know when he travels, and where does he go, if he likes spending his Saturdays at the museum or rather go to an indie concert. Sounds unreal right? Well, actually, as crazy as it seems, knowing a client that much is possible. Imagine now, how knowing that much about someone could help you giving the right information to your client, and help him taking the right decision at the right time.
 

Now the question you must ask yourself is how can you bring an added value to your client through an accurate customer knowledge? Customer knowledge being a real necessity today in order to boost sales.
 

The primary reasons why you need to reinforce your analytics on customers are the following:
 

  • Different business rules and new players: countless threads are coming from giants like Google, Facebook, Amazon or Apple who are starting to enter on the financial business, the same from niche players like Paypal, or even new digital business models based on Bitcoin currency.
  • The traditional business model is changing: revenue on banking industry is being affected dramatically by low interest rates, moderate fee revenue, tough regulations and an uncertainty worldwide economy. Thus, it will be more important than ever for banks to focus on all possible strategies to increase revenue and reduce costs.
  • Digital Channels: real-time and digital communications and interactions with customers are continuously growing, specially though mobile, Web and social networks, so it’s imperative to respond to this unstoppable migration to digital channels by channel transaction consolidation and, again, better customer knowledge.
     

A good and healthy customer knowledge approach is the foundation to a sustainable competitive advantage in banking, especially on Retail, so it’s time for banks to leverage the advances in processing, memory, database design and predictive analytic methods to really understand its customers. We should keep in mind that the cost of processing huge data volumes is no longer as much of a barrier as in the near past.
 

These are the 4 main Customer Analytics’ business drivers:
 

  • Customer Behavioral Insights: behavioral and attitudinal knowledge are key as channel selection and product use become more differentiated. It can be complemented by demographic and open data.
  • Business Strategy: Customer Analytics along with existing Business Intelligence systems (BI) allows organizations to take better decisions without the human bias, due to the fact that most of the insights are based on advanced analytical and predictive statistics models.
  • Customer Experience: delivering personalized, contextual interactions that will assist customers with their daily financial needs, plus, real-time delivery of product or service offerings at the right time.
  • Marketing: to increase the effectiveness and efficiency of sales and marketing by inferring the purchasing propensity based on both customer’s transactional and behavioral information. Rather than offering products and services based on predefined campaigns, Banks can make personalized offers for each individual customer.
     

The best way for a financial institution to leverage a high-value Customer Analytics approach should be first identifying the relevant business drivers and use case related to customer knowledge, prioritize them, and then think about how to acquire the capabilities.

 

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